If the y values are "hypergeometrically" distributed then they are
counts,
right? Loess is designed for continuous, reasonably symmetric data, and so
is inappropriate. You should probably consider GLM for a parametric fit; or
perhaps GAM for a nonparametric fit. As the data appear to have the
structure of a time series, you may wish to search CRAN for a non-Gaussian
time series package. I am unfamiliar with such methodology, so I have no
idea what, if anything, is available for this.
Better suggestion. Get help from a local statistician, at least to get you
started.
-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA
"The business of the statistician is to catalyze the scientific learning
process." - George E. P. Box
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Thomas L Jones
> Sent: Monday, December 19, 2005 5:53 AM
> To: R-project help
> Subject: [R] loess smoothing question
>
> I am trying to smooth a dataset with evenly spaced values of x,
> perhaps using loess smoothing or something similar. However, the y
> values are hypergeometrically distributed; I think I want to use a
> logarithmic link function. It falls under the general heading of
> non-parametric regression. The problem is of interest in predicting
> the demand at a voting place, in order to avoid long lines.
>
> Questions: Should I use loess smoothing?
> Do I want a logarithmic link function? If so,
> How do I tell loess to use a logarithmic link function?
>
> Tom, a newbie to the R project, and not really a statistician
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>